Further Development of an Ion current Combustion Control System (ICCS)

Further Development of an Ion current Combustion Control System (ICCS) Copyright 1998 Society of Automotive Engineers, Inc. Morito Asano, Atsushi Ito, Tetsuo Kuma, Mitsunobu Kajitani DAIHATSU Motor Co. Manabu Takeuchi, Yoshiyuki Fukumura, Mitsuhiro Izumi DIAMOND Electric Co. ABSTRACT As we developed Ion Current Combustion Control system (ICCS), we began to discover some issues of the ion current system. Depending upon combustion scenarios, the noise contributed to weak output characteristics and output variations making the combustion unstable. This paper intends to present methods developed to overcome these issues: SYSTEM HARDWARE In the previous report (1), we described the issues on the detection sensitivities and noise proof characteristics. In this study, we further reviewed the system component designs to address those challenges. SYSTEM SOFTWARE We have reported (1) a learning method for the stable knock control for varying output characteristics. However, there was a limitation in the application. Hence, we further analyzed the ion current characteristics, then developed a new algorithm to resolve this issue. This new system with the knock control and the misfire detection was introduced in 2000 MY. INTRODUCTION It is essential to adopt the advanced combustion control to meet the market demand of lower emission level and better fuel economy. We believed that creating a simple and compact system for the mass market was the key to this technology. We reported that the ion current had characteristics for the excellent combustion detection and could be applied to the fuel control and the spark advance control through the knock detection in our previous study. However, we also reported that the ion current signal level was relatively weak and could be influenced from its surroundings. Furthermore, the output performance might be influenced by the changing conditions; thus more device would have been needed to achieve a better control. These issues make the knock detection challenging, since it is very sensitive to a noise. These are points reported for the further study in our previous report. We also added more points to improve the detection accuracy in this study as well. We discovered that the learning method of stable knock control in changing output characteristics reported in the last study, has more challenges. In this study, we would like to share the new learning method and its effectiveness, and how we achieved the better knock control method with better accuracy even in presence of tolerance variances, the time gap, as well as other environmental condition changes. CONTROL SYSTEM OVERVIEW ENGINE SPECIFICATIONS Table 1 shows the specifications of the test engine used for developing ICCS. Table 1 Engine Specification Bore * Stroke (mm * mm) 72 * 79.7 Displacement (cc) 1298 Number of Cylinders Number of Valves(per cyl.) 4 Cylinders, In-Line 2 Intakes, 2 Exhausts Compression Ratio 10.0 Fuel System Ignition System (1) (2) (3) SYSTEM ARCHITECTURE Electric Controlled Fuel Injection Electric Controlled Single Distributor-Less Ignition The architecture of ICCS is shown in Figure 1. After the ignition discharge has been completed, the bias power is supplied to the center electrode of the ignition plug to detect the ion current. (4) To simplify the system architecture, a part of the accumulated energy from the ignition coil are used for this bias power. As the magnitude of the ion current detected by the above circuit is too small to input directly to ECU, the current is converted into the voltage through the charge amp and then the voltage is amplified. The power module

Fig.1 Ion Current Combustion Control System (ICCS) integrated with the ion charge amp shown in Figure 2 manipulates these processing. It is made by a Flip Chip (bare chip surface mount) process to cope with a high temperature condition under the hood and to be compact and to be lightweight. Moreover, this system can detect the ion current in each cylinder shown as in Figure 3 and it can also control combustion per cylinder. Fig.3 Individual Control System In order to increase the accuracy of the knock control, we focused on following: Spark Plug The center electrode, whose biased positive voltage collects electrons, needs enough surface area to detect the ion current. The plug (for example, in case of platinum plug) which has a thin electrode is unfavorable for the detection of the ion electric current. It is more preferable to use a plug with small insulator and projection of center electrode. Ignition Coil Fig.2 Igniter with Ion Charge Amp. The electric charge generated around the ignition coil can influence the ion current detection and it may even prevent the knocking signal detection. In order to counter this issue, we changed the external designs to minimize the affect from the electric charge. We discovered that modifying the system architecture could reduce such a negative affect.

Wiring An independent wiring is necessary to avoid the affects of electrical load variances. However, a shielded wire or an electro-static shield is needed to avoid the affects of the magnetic field. This is particularly essential in the knock control. The signal often is negatively affected because it also has noise-like characteristics of its own. Our system adopts the electro-static shield to improve the accuracy of the knocking signal detection. Although the integral ion signal process circuit in the ignition coil is preferable for its performance and the packaging, if this structure is not feasible, then the control method of the system can be utilized. Furthermore, through the analog circuits, the amplified signal is converted into the combustion signals for the misfire and the knock control and then directed to the CPU. Detailed explanations of the analog circuit for the knock control are provided in the following sections. KNOCK CONTROL The aim of this control is to detect the knocking signal and to control the ignition timing to prevent the knocking. The targets for this system are the circuit structure to detect a stable knocking signal avoiding the affect of the various environmental changes and variations of the circuit, and then to provide the algorithms for the precise knocking analyses. The analog circuit and the strategy for this control are as follow: ANALOG CIRCUIT Figure 4 shows how the ion current energy and frequency correspond to the cylinder pressure knocking frequency. (6)(7)(8) Therefore, we used the analog circuit shown in Figure 5. The ion current is filtered through the frequency band corresponding to the knocking and is then integrated. The integrated value is referred to as the knocking signal in this literature. Finally, the signal is directed to the CPU. The following countermeasures, shown in Figure 5, are taken to prevent the mis-detection. Fig.-5 Circuit Block Diagram for knock control Window signal The window signal is set only when there is a possibility that the knock could occur. The ion current is inputted to the band pass filter only when the window signal is set. The window interval is changed according to the engine speed and the load. Because the negative affects of the discharge need to be avoided, the detection range can further limited at higher engine speeds. Noise Detection Circuit If the ion current is measured along with the window signal and then passes through the band pass filter, then the noise would affect the detection accuracy. This is because a step signal input contains various frequency compositions including the knocking frequency. We added an edge restraint circuit with a slower time constant than the knocking frequency on the signal input to counter this issue. CONTROL STRATEGY In regards to the control strategy, the basic architecture is unchanged. However, we re-evaluated the architecture with a new learning method for the desired value calculation as follow: Fig.6 Block Diagram of Control Strategy for Knock Control Fig.4 Knocking Signal Figure 6 shows the architecture of the control strategy. As the controlled variable (knocking signal) follows the desired value (the averaged value of the knocking signal when knock has not occurred), the manipulated variable (ignition timing) is controlled. To adapt the tolerance of ICCS and circumstance change, the desired value is adapted. This controller also consists of the feed back and feed forward control.

Adaptation of Desired Value Importance of the Reference Value (Ref.-Value) in Calculation of the Desired Value The ion current waveform changes its gain due to various driving conditions or variations in the signal processing circuit. The knocking frequency composition contained in the ion current also would be changed along with the waveform change. In another words, the knocking detection strengths differ when the Ref.-Value for the knocking detection is constant. The Figure 7 shows Coefficient K (Desired Value = Ref.-Value * K) which is used to detect the medium knocking with a constant Ref.-Value to counter circuit variations. As you can see the K value differs when the Ref.-Value for the knocking judgment is constant. Then, it is necessary to learn the Ref.-Value when there is no knocking to calculate the Desired Value. Our previous report (1) covered the method to learn the Ref.-Value and to calculate the Desired Value = F (Ref.-Value) as follow: Fig.8 Variation Rate of Knocking Signal Fig.9 Flowchart of Calculation of Desired Value (1) Fig.7 Coefficient K Vs Variation of Such as Circuit Ref.-Value Calculation in the Previous Report and its Limitations. Figure 8 shows the analyzed result of the variation rate of the knocking signal when the knocking level is changed. The variation rate is very low when the knock does not occur, but becomes greater when the knock occurs. However, the variation rate is not influenced by the knocking intensity. This means that the variation rate of the knocking signal makes it possible to distinguish a knocking from "no" knocking. Therefore, we adapted the Desired Value calculated according to the flow chart shown in Figure 9. The Desired Value is re-calculated only when the variation rate of the knocking signal is lower than the reference value. This method enables the system to learn no knocking signal as the Ref.-Value. However, the Ref.-Value (an average or a dispersion) differs at different engine conditions as shown in Figure 10, and it is necessary to set a matrix area for the different load conditions and to learn the Ref.-Value for each area. Then again, a driver does not always use all the operation areas. In another words, the method to calculate the Desired Value using only the Ref.-Value in the learned area, is complicated and can be difficult. Fig.10 Ref.-Value in Various Operation Conditions (Average and Dispersion)

This finding lead the study to conclude that a simple learning method that would enable the system to determine the Ref.-Value in all operating areas is needed. New Calculation Algorithms In order to resolve the issue stated above, we studied the method to calculate the Ref.-Value when there was no knocking condition. This is to compensate for the various driving conditions as well as variations of the ion current. As we investigated a relationship between the knocking signal level and the ion current waveform characteristics from various aspects, we were able to establish a correlation. Figure 11 shows the relationship between the peak value of the ion current and the intergrated value of knocking signal when all of operating conditions without knocking and the lower limits to the circuit variances are imposed. The knocking signal level contained in the ion current when there is no knock can be proximate by a function. This is because the knocking signal composition is contained in the ion current as a purely electrical composition. And this relationship seems to be established whether or not the knock exists. Base on this finding, we concluded that it is not necessary to learn all operation areas, but instead, the Ref.-Value can be calculated by the ion current peak value. Figure 13 shows the relationship when the knock occurs. Fig.13 Knocking Signal and Ion Current (3) Fig. 11 Knocking Signal and Ion Current (1) The knocking signal shown when a knocking exists is far more wide spread compare to the no knock condition. This means that we can detect the knocking because the signal would be several coefficient times away from the ideal condition. Figure 14 shows the flow chart for the calculation of the Desired Value. Although there are some variances, two factors clearly have a direct correlation. Figure 12 also shows the direct correlation when all of operating conditions without knocking and the upper limits to the circuit variances are imposed. Fig.14 Flowchart of Calculation of Desired Value (2) Fig.12 Knocking Signal and Ion Current (2) In addition, we have conducted another study for the white noise factor (included in the previous report) which is present in the ion current waveform. This factor is applied as an offset value into the Desire Value to counter this issue.

Feed Back Control We calculate the correction term by using the conventional integration control. The deviation for the integration control is a difference between the controlled variable (the integrated value of knocking signal) and the Desired Value ( the calculated by Ref.-Value). However, there are some issues in the knock control using the ion current. In case of excessive spark timing retard in control, the combustion gets worse and the ion current waveform becomes distorted. It would sometimes contain the knocking frequency composition resulting in mis-detection of knocking. In order to resolve this issue, we set the spark retard which is limited by variation of combustion. Feed Forward Control The Feed forward correction term consists of the only base ignition timing which is calculated from the engine speed and the load. EFFECTIVENESS OF NEW LEARNING ALGORITHM This control method enables calculation of the Ref.-Value without a need to learn all operation areas using the ion current. Because it calculates the Desire Value at each ignition timing per cylinder, it does not require a long adjustment time for the Ref.-Value, and it can accommodate drastic changes in the combustion environment. Next, we will show the K value, utilizing the method above, which is used to control the medium knocking. Figure 15 shows the upper and the lower limits of circuit variations, and Figure 16 shows variations from the plug ware. Both charts indicate that K value remains relatively consistent with the variations of the control circumstances including the circuit. In brief, this control method enables a stable control without variances from the circuit output and other factors indicated by utilizing the standard specification tuning. Fig.16 Effectiveness of New Learning Algorithm (2) CONCLUSION HARDWARE It is necessary to examine the optimum architecture such as an ignition coil, a spark plug and a wiring to avoid the external influences on a weak ion current to achieve the stable knocking signal detection. The knocking signal containing the ion current has electrical characteristics. The Ref.-Value can be calculated from the function using the ion current waveform. Then this enables the system to avoid the influences such as the circuit variations. Because it calculates the Desired Value at each spark timing per cylinder, we can achieve the consistent and the stable control even in unstable and drastic conditions. Fig.15 Effectiveness of New Learning Algorithm (1)

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